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DBMS > EsgynDB vs. Google Cloud Bigtable vs. PouchDB vs. Riak KV

System Properties Comparison EsgynDB vs. Google Cloud Bigtable vs. PouchDB vs. Riak KV

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonPouchDB  Xexclude from comparisonRiak KV  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.JavaScript DBMS with an API inspired by CouchDBDistributed, fault tolerant key-value store
Primary database modelRelational DBMSKey-value store
Wide column store
Document storeKey-value store infowith links between data sets and object tags for the creation of secondary indexes
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score2.28
Rank#115  Overall
#21  Document stores
Score4.10
Rank#82  Overall
#9  Key-value stores
Websitewww.esgyn.cncloud.google.com/­bigtablepouchdb.com
Technical documentationcloud.google.com/­bigtable/­docspouchdb.com/­guideswww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperEsgynGoogleApache Software FoundationOpenSource, formerly Basho Technologies
Initial release2015201520122009
Current release7.1.1, June 20193.2.0, December 2022
License infoCommercial or Open SourcecommercialcommercialOpen SourceOpen Source infoApache version 2, commercial enterprise edition
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaJavaScriptErlang
Server operating systemsLinuxhostedserver-less, requires a JavaScript environment (browser, Node.js)Linux
OS X
Data schemeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesnonono
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nononono
Secondary indexesyesnoyes infovia viewsrestricted
SQL infoSupport of SQLyesnonono
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP REST infoonly for PouchDB Server
JavaScript API
HTTP API
Native Erlang Interface
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
JavaScriptC infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresJava Stored ProceduresnoView functions in JavaScriptErlang
Triggersnonoyesyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infowith a proxy-based framework, named couchdb-loungeSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnonono infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noyes, using Riak Security

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More resources
EsgynDBGoogle Cloud BigtablePouchDBRiak KV
DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
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